The DPC-Based Scheme for Detecting Selective Forwarding in Clustered Wireless Sensor Networks

Jingze Ding,Zixian Guo,Yuanming Wu,Haotian Zhang

doi:10.1109/access.2021.3055026

Abstract

Many studies have shown that clustered Wireless Sensor Networks (WSNs) have a better performance in terms of the balance of energy and lifetime. However, due to the harsh environment and open communication, the clustered WSNs are easy to be attacked. The selective forwarding attack is one of the most difficult attacks to be detected. When a malicious sensor node launches the selective forwarding attacks, it drops part of or all the data packets it received. In this paper, we propose a Noise-Based Density Peaks Clustering (NB-DPC) algorithm for detecting selective forwarding attacks. It can detect selective forwarding attacks by clustering the Cumulative Forwarding Rates (CFRs) of all sensor nodes. The NB-DPC algorithm has been improved by defining noise points specifically for identifying malicious behavior and deleting the unnecessary steps in Density Peaks Clustering (DPC) for faster detection speed. The NB-DPC has a low Missed Detection Rate (MDR) and False Detection Rate (FDR) of below 1% according to the simulation results.

Highlights

As one of the emerging technologies, Wireless Sensor Networks (WSNs) have a broad market in the military and civilian domain, highlighting the need of securing these networks
1) DETECTION RESULTS COMPARED WITH OTHER DCAS We compare the clustering results of Noise-Based Density Peaks Clustering (NB-Density Peaks Clustering (DPC)) with DP-Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-means in terms of the Missed Detection Rate (MDR) and False Detection Rate (FDR)
2) DETECTION RESULTS COMPARED WITH OTHER SCHEMES We compare NB-DPC with the watchdog mechanism [45], neighbor-based monitoring scheme [46], and Inspector Nodes (INs)-monitoring scheme [6] with the rate of the malicious node set to 10% in terms of MDR and FDR

Summary

Introduction

As one of the emerging technologies, Wireless Sensor Networks (WSNs) have a broad market in the military and civilian domain, highlighting the need of securing these networks. Sensor nodes in clustered WSNs are tender to different types of attacks (sinkhole attack, selective forwarding attack, and so on) because of the limited capability of calculating and storing, and they are vulnerable because of open communication and being unguarded [1]–[3]. The sinkhole attack causes serious damage by blocking the data transmission between sensor nodes and the sink nodes [4]. The selective forwarding attack is one of the most important internal attacks, which refers to a kind of attack where nodes compromised by the attacker drop all or part of the data packets [5]. Malicious nodes behave cunningly and drop packets randomly, while. Poor channel quality can cause nodes unable to forward packets successfully [6].

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Results

Conclusion